Copper and lead removal by peanut hulls: equilibrium and kinetic studies

This research work aims to study the use of peanut hulls, an agricultural and food industry waste, for copper and lead removal through equilibrium and kinetic parameters evaluation. Equilibrium batch studies were performed in a batch adsorber. The influence of initial pH was evaluated (3–5) and it was selected between 4.0 and 4.5. The maximum sorption capacities obtained for the Langmuir model were 0.21 ± 0.03 and 0.18 ± 0.02 mmol/g, respectively for copper and lead. In bi-component systems, competitive sorption of copper and lead was verified, the total amount adsorbed being around 0.21 mmol of metal per gram of material in both mono and bi-component systems. In the kinetic studies equilibrium was reached after 200 min contact time using a 400 rpm stirring rate, achieving 78% and 58% removal, in mono-component system, for copper and lead respectively. Their removal follows a pseudo-second-order kinetics. These studies show that most of the metals removal occurred in the first 20 min of contact, which shows a good uptake rate in all systems

Copper, nickel and zinc removal by peanut hulls: batch and column studies in mono, tri-component systems and with real effluent

The main goal of this research study was the removal of Cu(II), Ni(II) and Zn(II) from aqueous solutions using peanut hulls. This work was mainly focused on the following aspects: chemical characterization of the biosorbent, kinetic studies, study of the pH influence in mono-component systems, equilibrium isotherms and column studies, both in mono and tri-component systems, and with a real industrial effluent from the electroplating industry. The chemical characterization of peanut hulls showed a high cellulose (44.8%) and lignin (36.1%) content, which favours biosorption of metal cations. The kinetic studies performed indicate that most of the sorption occurs in the first 30 min for all systems. In general, a pseudo-second order kinetics was followed, both in mono and tri-component systems. The equilibrium isotherms were better described by Freundlich model in all systems. Peanut hulls showed higher affinity for copper than for nickel and zinc when they are both present. The pH value between 5 and 6 was the most favourable for all systems. The sorbent capacity in column was 0.028 and 0.025 mmol g-1 for copper, respectively in mono and tri-component systems. A decrease of capacity for copper (50%) was observed when dealing with the real effluent. The Yoon-Nelson, Thomas and Yan’s models were fitted to the experimental data, being the latter the best fit

Validation of a capillary zone electrophoresis method for the determination of ciprofloxacin, gatifloxacin, moxifloxacin and ofloxacin in pharmaceutical formulations

An alternative capillary zone electrophoresis (CZE) method for the determination of ciprofloxacin (CPFLX), gatifloxacin (GTFLX), moxifloxacin (MFLX) and ofloxacin (OFLX) through a simple aqueous electrolyte system consisting of 25 mmol L-1 of TRIS/ hydrochloride and 15 mmol L-1 of sodium tetraborate buffer mixture (pH 8.87) using direct UV detection at 282 nm within 3 min was validated. The analytical parameters of validation evaluated were: linearity (r > 0.998), selectivity (comparison between slope of the calibration curve of external standard and calibration curve of standard addition), repeatability in area for sample (RSD%: < 3.94% for CPFLX, < 3.87% for GTFLX, 1.30% for MFLX and < 1.88% for OFLX), intermediate precision in area for sample (RSD%: < 3.59% for CPFLX, < 3.09% for GTFLX, 2.67% for MFLX and < 2.25% for OFLX), accuracy (mean of recovery range: 101.2% for CPFLX, 101.0% for GTFLX, 101.3% for MFLX and 99.9% for OFLX), limit of detection (mg L-1: 2.72 for CPFLX, 1.92 for GTFLX, 0.795 for MFLX and 1.05 for OFLX), limit of quantification (mg L-1: 9.06 for CPFLX, 6.40 for GTFLX, 2.65 for MFLX and 3.50 for OFLX) and robustness. Due to its simplicity, selectivity, precision, accuracy and rapidity, the methodology can be an interesting alternative for quality assurance in the pharmaceutical industry of these drugs

Degradation prediction model for friction in highways

The purpose of this paper is to develop a multiple linear regression model that describes the pavement’s friction behaviour using a degradation evo- lution law that also considers the effects of weather, vertical alignment and traf- fic factors. This study is based on real data obtained from two different highways with an approximate total length of 43 km. These sections present different alignment features (plan/profile), different Annual Average Daily Traffic and are subject- ed to different weather conditions. Nevertheless, both comprise the same type of upper layer. The efficiency of the linear regression model in approaching and explaining da- ta was demonstrated. The most relevant factors involved in the degradation pro- cess of pavements’ friction were identified.Fundação para a Ciência e a Tecnologia (FCT

Interplay between the salience and the default mode network in a social-cognitive task toward a close other

Social cognition relies on two main subsystems to construct the understanding of others, which are sustained by different social brain networks. One of these social networks is the default mode network (DMN) associated with the socio-cognitive subsystem (i.e., mentalizing), and the other is the salience network (SN) associated with the socio-affective route (i.e., empathy). The DMN and the SN are well-known resting state networks that seem to constitute a baseline for the performance of social tasks. We aimed to investigate both networks' functional connectivity (FC) pattern in the transition from resting state to social task performance. A sample of 38 participants involved in a monogamous romantic relationship completed a questionnaire of dyadic empathy and underwent an fMRI protocol that included a resting state acquisition followed by a task in which subjects watched emotional videos of their romantic partner and elaborated on their partner's (Other condition) or on their own experience (Self condition). Independent component and ROI-to-ROI correlation analysis were used to assess alterations in task-independent (Rest condition) and task-dependent (Self and Other conditions) FC. We found that the spatial FC maps of the DMN and SN evidenced the traditional regions associated with these networks in the three conditions. Anterior and posterior DMN regions exhibited increased FC during the social task performance compared to resting state. The Other condition revealed a more limited SN's connectivity in comparison to the Self and Rest conditions. The results revealed an interplay between the main nodes of the DMN and the core regions of the SN, particularly evident in the Self and Other conditions.info:eu-repo/semantics/publishedVersio

Vagococcus fluvialis isolation and sequencing from urine of healthy cattle

While the gram-positive bacterium Vagococcus fluvialis has been isolated from the environment as well as fish, birds, and mammals, very little is known about the species. V. fluvialis is believed to be a probiotic in fishes. However, within mammals, it is more frequently isolated from infectious tissue, including on rare occasions human and livestock lesions. Prior to the study described here, V. fluvialis had never been found in healthy bovine animals. Here, we present the complete genomes of V. fluvialis UFMG-H6, UFMG-H6B, and UFMG-H7, novel strains isolated from urine samples from healthy bovine females. These are the first genomes of mammalian isolates and the first description of V. fluvialis from urine. The genomes did not encode for any known virulence genes, suggesting that they may be commensal members of the urine microbiota

Escherichia coli and Pseudomonas aeruginosa Isolated From Urine of Healthy Bovine Have Potential as Emerging Human and Bovine Pathogens

The study of livestock microbiota has immediate benefits for animal health as well as mitigating food contamination and emerging pathogens. While prior research has indicated the gastrointestinal tract of cattle as the source for many zoonoses, including Shiga-toxin producing Escherichia coli and antibiotic resistant bacteria, the bovine urinary tract microbiota has yet to be thoroughly investigated. Here, we describe 5 E. coli and 4 Pseudomonas aeruginosa strains isolated from urine of dairy Gyr cattle. While both species are typically associated with urinary tract infections and mastitis, all of the animals sampled were healthy. The bovine urinary strains were compared to E. coli and P. aeruginosa isolates from other bovine samples as well as human urinary samples. While the bovine urinary E. coli isolates had genomic similarity to isolates from the gastrointestinal tract of cattle and other agricultural animals, the bovine urinary P. aeruginosa strains were most similar to human isolates suggesting niche adaptation rather than host adaptation. Examination of prophages harbored by these bovine isolates revealed similarity with prophages within distantly related E. coli and P. aeruginosa isolates from the human urinary tract. This suggests that related urinary phages may persist and/or be shared between mammals. Future studies of the bovine urinary microbiota are needed to ascertain if E. coli and P. aeruginosa are resident members of this niche and/or possible sources for emerging pathogens in humans

Prediction of friction degradation in highways with linear mixed models

The development of a linear mixed model to describe the degradation of friction on flexible road pavements to be included in pavement management systems is the aim of this study. It also aims at showing that, at the network level, factors such as temperature, rainfall, hypsometry, type of layer, and geometric alignment features may influence the degradation of friction throughout time. A dataset from six districts of Portugal with 7204 sections was made available by the Ascendi Concession highway network. Linear mixed models with random effects in the intercept were developed for the two-level and three-level datasets involving time, section and district. While the three-level models are region-specific, the two-level models offer the possibility to be adopted to other areas. For both levels, two approaches were made: One integrating into the model only the variables inherent to traffic and climate conditions and the other including also the factors intrinsic to the highway characteristics. The prediction accuracy of the model was improved when the variables hypsometry, geometrical features, and type of layer were considered. Therefore, accurate predictions for friction evolution throughout time are available to assist the network manager to optimize the overall level of road safety.This research was funded by FCT—Fundação para a Ciência e Tecnologia (Foundation for Science and Technology), Grants No. UIDB/04029/2020 and UIDB/00319/2020

Application of Nanostructured Carbon-Based Electrochemical (Bio)Sensors for Screening of Emerging Pharmaceutical Pollutants in Waters and Aquatic Species: A Review

Pharmaceuticals, as a contaminant of emergent concern, are being released uncontrollably into the environment potentially causing hazardous effects to aquatic ecosystems and consequently to human health. In the absence of well-established monitoring programs, one can only imagine the full extent of this problem and so there is an urgent need for the development of extremely sensitive, portable, and low-cost devices to perform analysis. Carbon-based nanomaterials are the most used nanostructures in (bio)sensors construction attributed to their facile and well-characterized production methods, commercial availability, reduced cost, high chemical stability, and low toxicity. However, most importantly, their relatively good conductivity enabling appropriate electron transfer rates—as well as their high surface area yielding attachment and extraordinary loading capacity for biomolecules—have been relevant and desirable features, justifying the key role that they have been playing, and will continue to play, in electrochemical (bio)sensor development. The present review outlines the contribution of carbon nanomaterials (carbon nanotubes, graphene, fullerene, carbon nanofibers, carbon black, carbon nanopowder, biochar nanoparticles, and graphite oxide), used alone or combined with other (nano)materials, to the field of environmental (bio)sensing, and more specifically, to pharmaceutical pollutants analysis in waters and aquatic species. The main trends of this field of research are also addressed.This work was financially supported by: projects UID/QUI/50006/2019 and PTDC/ASP-PES/29547/2017 (POCI-01-0145-FEDER-029547) funded by FEDER funds through the POCI and by National Funds through FCT - Foundation for Science and Technology. This proposal was also subsidized by the Brazilian agencies CNPq (Proc. 420261/2018-4) and CAPES (Proc. 88881.140821/2017-01; Finance code 001). F.W.P. Ribeiro acknowledges funding provided by FUNCAP-BPI (Proc. BP3-0139-00301.01.00/18). Acknowledgments T.M.B.F. Oliveira thanks the UFCA’s Pro-Rectory of Research and Innovation for initiating his investigations. F.W.P. Ribeiro thanks the CNPq (proc. 406135/2018-5) and all support provided by the UFCA‘s Pro-Rectory of Research and Innovation. A.N. Correia thanks the CNPq (proc. 305136/2018-6).info:eu-repo/semantics/publishedVersio